A Nonmonotone Trust Region Algorithm for Nonlinear Optimization Subject to General Constraints

A Nonmonotone Trust Region Algorithm for Nonlinear Optimization Subject to General Constraints

Year:    2003

Journal of Computational Mathematics, Vol. 21 (2003), Iss. 2 : pp. 237–246

Abstract

In this paper we present a nonmonotone trust region algorithm for general nonlinear constrained optimization problems. The main idea of this paper is to combine Yuan's technique [1] with a nonmonotone method similar to Ke and Han [2]. This new algorithm may not only keep the robust properties of the algorithm given by Yuan, but also have some advantages led by the nonmonotone technique. Under very mild conditions, global convergence for the algorithm is given. Numerical experiments demonstrate tre efficiency of the algorithm.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/2003-JCM-10278

Journal of Computational Mathematics, Vol. 21 (2003), Iss. 2 : pp. 237–246

Published online:    2003-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    10

Keywords:    Nonlinear optimization Nonmonotone algorithm Trust region General constraints.